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Reviews different machine learning and deep learning techniques
with a biomedical perspective Provides the relevant case studies
that demonstrate applicability of different AI techniques Explain
different kinds of inputs like various image modalities, biomedical
signals types, etc. Covers the latest trends of AI-based biomedical
domains including IoT, drug discovery, biomechanics, robotics,
electronic health records, etc. Discusses the research challenges
and opportunities in AI and biomedical domain
Computational Intelligence and Deep Learning Methods for
Neuro-rehabilitation Applications explores the different
possibilities of providing AI based neuro-rehabilitation methods to
treat neurological disorders. This book provides in-depth knowledge
on the challenges and solutions associated with the different
varieties of neuro-rehabilitation through the inclusion of case
studies and real-time scenarios in different geographical
locations. Beginning with an overview of neuro-rehabilitation
applications, the book discusses the role of machine learning
methods in brain function grading for adults with Mild Cognitive
Impairment, Brain Computer Interface for post-stroke patients,
developing assistive devices for paralytic patients, and cognitive
treatment for spinal cord injuries. Topics also include
AI-based video games to improve the brain performances in children
with autism and ADHD, deep learning approaches and
magnetoencephalography data for limb movement, EEG signal analysis,
smart sensors, and the application of robotic concepts for gait
control.
Computational Intelligence and Modelling Techniques for Disease
Detection in Mammogram Images comprehensively examines the wide
range of AI-based mammogram analysis methods for medical
applications. Beginning with an introductory overview of mammogram
data analysis, the book covers the current technologies such as
ultrasound, molecular breast imaging (MBI), magnetic resonance
(MR), and Positron Emission mammography (PEM), as well as the
recent advancements in 3D breast tomosynthesis and 4D mammogram.
Deep learning models are presented in each chapter to show how they
can assist in the efficient processing of breast images. The book
also discusses hybrid intelligence approaches for early-stage
detection and the use of machine learning classifiers for cancer
detection, staging and density assessment in order to develop a
proper treatment plan. This book will not only aid computer
scientists and medical practitioners in developing a real-time AI
based mammogram analysis system, but also addresses the issues and
challenges with the current processing methods which are not
conducive for real-time applications.
This book is a detailed reference on biomedical applications using
Deep Learning. Because Deep Learning is an important actor shaping
the future of Artificial Intelligence, its specific and innovative
solutions for both medical and biomedical are very critical. This
book provides a recent view of research works on essential, and
advanced topics. The book offers detailed information on the
application of Deep Learning for solving biomedical problems. It
focuses on different types of data (i.e. raw data, signal-time
series, medical images) to enable readers to understand the
effectiveness and the potential. It includes topics such as disease
diagnosis, image processing perspectives, and even genomics. It
takes the reader through different sides of Deep Learning oriented
solutions. The specific and innovative solutions covered in this
book for both medical and biomedical applications are critical to
scientists, researchers, practitioners, professionals, and
educations who are working in the context of the topics.
This book emphasizes recent advances in the creation of biometric
identification systems for various applications in the field of
human activity. The book displays the problems that arise in modern
systems of biometric identification, as well as the level of
development and prospects for the introduction of biometric
technologies. The authors classify biometric technologies into two
groups, distinguished according to the type of biometric
characteristics used. The first group uses static biometric
parameters: fingerprints, hand geometry, retina pattern, vein
pattern on the finger, etc. The second group uses dynamic
parameters for identification: the dynamics of the reproduction of
a signature or a handwritten keyword, voice, gait, dynamics of work
on the keyboard, etc. The directions of building information
systems that use automatic personality identification based on the
analysis of unique biometric characteristics of a person are
discussed. The book is intended for professionals working and
conducting research in the field of intelligent information
processing, information security, and robotics and in the field of
real-time identification systems. The book contains examples and
problems/solutions throughout.
This book features a collection of high-quality research papers
presented at the International Conference on Advanced Computing
Technology (ICACT 2020), held at the SRM Institute of Science and
Technology, Chennai, India, on 23-24 January 2020. It covers the
areas of computational intelligence, artificial intelligence,
machine learning, deep learning, big data, and applications of
artificial intelligence in networking, IoT and bioinformatics
This book includes original research findings in the field of
memetic algorithms for image processing applications. It gathers
contributions on theory, case studies, and design methods
pertaining to memetic algorithms for image processing applications
ranging from defence, medical image processing, and surveillance,
to computer vision, robotics, etc. The content presented here
provides new directions for future research from both theoretical
and practical viewpoints, and will spur further advances in the
field.
Human-computer interaction (HCI) is one of the most significant
areas of computational intelligence. This book focuses on the human
emotion analysis aspects of HCI, highlighting innovative
methodologies for emotion analysis by machines/computers and their
application areas. The methodologies are presented with numerical
results to enable researchers to replicate the work. This
multidisciplinary book is useful to researchers and academicians,
as well as students wanting to pursue a career in computational
intelligence. It can also be used as a handbook, reference book,
and a textbook for short courses.
This book features a collection of high-quality research papers
presented at the International Conference on Advanced Computing
Technology (ICACT 2020), held at the SRM Institute of Science and
Technology, Chennai, India, on 23-24 January 2020. It covers the
areas of computational intelligence, artificial intelligence,
machine learning, deep learning, big data, and applications of
artificial intelligence in networking, IoT and bioinformatics
This book includes original research findings in the field of
memetic algorithms for image processing applications. It gathers
contributions on theory, case studies, and design methods
pertaining to memetic algorithms for image processing applications
ranging from defence, medical image processing, and surveillance,
to computer vision, robotics, etc. The content presented here
provides new directions for future research from both theoretical
and practical viewpoints, and will spur further advances in the
field.
This book focuses on the emerging advances in distributed
communication systems, big data, intelligent computing and Internet
of Things, presenting state-of-the-art research in frameworks,
algorithms, methodologies, techniques and applications associated
with data engineering and wireless distributed communication
technologies. In addition, it discusses potential topics like
performance analysis, wireless communication networks, data
security and privacy, human computer interaction, 5G Networks, and
smart automated systems, which will provide insights for the
evolving data communication technologies. In a nutshell, this
proceedings book compiles novel and high-quality research that
offers innovative solutions for communications in IoT networks.
As general, this book is a collection of the most recent, quality
research papers regarding applications of Artificial Intelligence
and Applied Mathematics for engineering problems. The papers
included in the book were accepted and presented in the 4th
International Conference on Artificial Intelligence and Applied
Mathematics in Engineering (ICAIAME 2022), which was held in Baku,
Azerbaijan (Azerbaijan Technical University) between May 20 and 22,
2022. Objective of the book content is to inform the international
audience about the cutting-edge, effective developments and
improvements in different engineering fields. As a collection of
the ICAIAME 2022 event, the book gives consideration for the
results by especially intelligent system formations and the
associated applications. The target audience of the book is
international researchers, degree students, practitioners from
industry, and experts from different engineering disciplines.
This book gathers selected papers presented at the
5th International Conference on Intelligent Data
Communication Technologies and Internet of Things (ICICI 2021),
organized by JCT College of Engineering and Technology, Coimbatore,
Tamil Nadu, India during 27 – 28 August 2021. This book solicits
the innovative research ideas and solutions for almost all the
intelligent data intensive theories and application domains. The
general scope of this book covers the design, architecture,
modeling, software, infrastructure and applications of intelligent
communication architectures and systems for big data or
data-intensive applications. In particular, this book reports the
novel and recent research works on big data, mobile and wireless
networks, artificial intelligence, machine learning, social network
mining, intelligent computing technologies, image analysis,
robotics and autonomous systems, data security and privacy.
Intelligent Edge Computing for Cyber Physical Applications
introduces state-of-the-art research methodologies, tools and
techniques, challenges, and solutions with further research
opportunities in the area of edge-based cyber-physical systems. The
book presents a comprehensive review of recent literature and
analysis of different techniques for building edge-based CPS. In
addition, it describes how edge-based CPS can be built to
seamlessly interact with physical machines for optimal performance,
covering various aspects of edge computing architectures for
dynamic resource provisioning, mobile edge computing, energy saving
scenarios, and different security issues. Sections feature
practical use cases of edge-computing which will help readers
understand the workings of edge-based systems in detail, taking
into account the need to present intellectual challenges while
appealing to a broad readership, including academic researchers,
practicing engineers and managers, and graduate students.
This book looks at the growing segment of Internet of Things
technology (IoT) known as Internet of Medical Things (IoMT), an
automated system that aids in bridging the gap between isolated and
rural communities and the critical healthcare services that are
available in more populated and urban areas. Many technological
aspects of IoMT are still being researched and developed, with the
objective of minimizing the cost and improving the performance of
the overall healthcare system. This book focuses on innovative IoMT
methods and solutions being developed for use in the application of
healthcare services, including post-surgery care, virtual home
assistance, smart real-time patient monitoring, implantable sensors
and cameras, and diagnosis and treatment planning. It also examines
critical issues around the technology, such as security
vulnerabilities, IoMT machine learning approaches, and medical data
compression for lossless data transmission and archiving. Internet
of Medical Things is a valuable reference for researchers,
students, and postgraduates working in biomedical, electronics, and
communications engineering, as well as practicing healthcare
professionals.
This book gathers selected papers presented at the 5th
International Conference on Intelligent Data Communication
Technologies and Internet of Things (ICICI 2021), organized by JCT
College of Engineering and Technology, Coimbatore, Tamil Nadu,
India during 27 - 28 August 2021. This book solicits the innovative
research ideas and solutions for almost all the intelligent data
intensive theories and application domains. The general scope of
this book covers the design, architecture, modeling, software,
infrastructure and applications of intelligent communication
architectures and systems for big data or data-intensive
applications. In particular, this book reports the novel and recent
research works on big data, mobile and wireless networks,
artificial intelligence, machine learning, social network mining,
intelligent computing technologies, image analysis, robotics and
autonomous systems, data security and privacy.
Handbook of Decision Support Systems for Neurological Disorders
provides readers with complete coverage of advanced computer-aided
diagnosis systems for neurological disorders. While computer-aided
decision support systems for different medical imaging modalities
are available, this is the first book to solely concentrate on
decision support systems for neurological disorders. Due to the
increase in the prevalence of diseases such as Alzheimer,
Parkinson's and Dementia, this book will have significant
importance in the medical field. Topics discussed include recent
computational approaches, different types of neurological
disorders, deep convolution neural networks, generative adversarial
networks, auto encoders, recurrent neural networks, and
modified/hybrid artificial neural networks.
Wearable Telemedicine Technology for the Healthcare Industry:
Product Design and Development focuses on recent advances and
benefits of wearable telemedicine techniques for remote health
monitoring and prevention of chronic conditions, providing real
time feedback and help with rehabilitation and biomedical
applications. Readers will learn about various techniques used by
software engineers, computer scientists and biomedical engineers to
apply intelligent systems, artificial intelligence, machine
learning, virtual reality and augmented reality to gather,
transmit, analyze and deliver real-time clinical and biological
data to clinicians, patients and researchers. Wearable telemedicine
technology is currently establishing its place with large-scale
impact in many healthcare sectors because information about patient
health conditions can be gathered anytime and anywhere outside of
traditional clinical settings, hence saving time, money and even
lives.
This book looks at the growing segment of Internet of Things
technology (IoT) known as Internet of Medical Things (IoMT), an
automated system that aids in bridging the gap between isolated and
rural communities and the critical healthcare services that are
available in more populated and urban areas. Many technological
aspects of IoMT are still being researched and developed, with the
objective of minimizing the cost and improving the performance of
the overall healthcare system. This book focuses on innovative IoMT
methods and solutions being developed for use in the application of
healthcare services, including post-surgery care, virtual home
assistance, smart real-time patient monitoring, implantable sensors
and cameras, and diagnosis and treatment planning. It also examines
critical issues around the technology, such as security
vulnerabilities, IoMT machine learning approaches, and medical data
compression for lossless data transmission and archiving. Internet
of Medical Things is a valuable reference for researchers,
students, and postgraduates working in biomedical, electronics, and
communications engineering, as well as practicing healthcare
professionals.
This book emphasizes recent advances in the creation of biometric
identification systems for various applications in the field of
human activity. The book displays the problems that arise in modern
systems of biometric identification, as well as the level of
development and prospects for the introduction of biometric
technologies. The authors classify biometric technologies into two
groups, distinguished according to the type of biometric
characteristics used. The first group uses static biometric
parameters: fingerprints, hand geometry, retina pattern, vein
pattern on the finger, etc. The second group uses dynamic
parameters for identification: the dynamics of the reproduction of
a signature or a handwritten keyword, voice, gait, dynamics of work
on the keyboard, etc. The directions of building information
systems that use automatic personality identification based on the
analysis of unique biometric characteristics of a person are
discussed. The book is intended for professionals working and
conducting research in the field of intelligent information
processing, information security, and robotics and in the field of
real-time identification systems. The book contains examples and
problems/solutions throughout.
Telemedicine Technologies: Big Data, Deep Learning, Robotics,
Mobile and Remote Applications for Global Healthcare illustrates
the innovative concepts, methodologies and frameworks that will
increase the feasibility of the existing telemedicine system. The
book also focuses on showcasing prototypes of remote healthcare
systems, thus emphasizing the data processing side that is often
recognized as the backbone of any telemedicine system.
Computational Methods and Deep Learning for Ophthalmology presents
readers with the concepts and methods needed to design and use
advanced computer-aided diagnosis systems for ophthalmologic
abnormalities in the human eye. Chapters cover computational
approaches for diagnosis and assessment of a variety of
ophthalmologic abnormalities. Computational approaches include
topics such as Deep Convolutional Neural Networks, Generative
Adversarial Networks, Auto Encoders, Recurrent Neural Networks, and
modified/hybrid Artificial Neural Networks. Ophthalmological
abnormalities covered include Glaucoma, Diabetic Retinopathy,
Macular Degeneration, Retinal Vein Occlusions, eye lesions,
cataracts, and optical nerve disorders. This handbook provides
biomedical engineers, computer scientists, and multidisciplinary
researchers with a significant resource for addressing the increase
in the prevalence of diseases such as Diabetic Retinopathy,
Glaucoma, and Macular Degeneration.
Human-computer interaction (HCI) is one of the most significant
areas of computational intelligence. This book focuses on the human
emotion analysis aspects of HCI, highlighting innovative
methodologies for emotion analysis by machines/computers and their
application areas. The methodologies are presented with numerical
results to enable researchers to replicate the work. This
multidisciplinary book is useful to researchers and academicians,
as well as students wanting to pursue a career in computational
intelligence. It can also be used as a handbook, reference book,
and a textbook for short courses.
This book brings together the most recent, quality research papers
accepted and presented in the 3rd International Conference on
Artificial Intelligence and Applied Mathematics in Engineering
(ICAIAME 2021) held in Antalya, Turkey between 1-3 October 2021.
Objective of the content is to provide important and innovative
research for developments-improvements within different engineering
fields, which are highly interested in using artificial
intelligence and applied mathematics. As a collection of the
outputs from the ICAIAME 2021, the book is specifically considering
research outcomes including advanced use of machine learning and
careful problem designs on human-centred aspects. In this context,
it aims to provide recent applications for real-world improvements
making life easier and more sustainable for especially humans. The
book targets the researchers, degree students, and practitioners
from both academia and the industry.
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